About this blog
Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. His areas of expertise include computational statistics, statistical graphics, statistical simulation, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
Follow @RickWicklin on Twitter.
Subscribe to this blog
Tags9.3 9.4 9.22 12.1 12.3 13.1 13.2 Bootstrap and Resampling Ciphers Conferences Data Analysis Efficiency File Exchange Getting Started GTL Heat maps History IMLPlus Just for Fun Math Matrix Computations Numerical Analysis Optimization R Reading and Writing Data SAS/IML Studio SAS Programming Simulation Statistical Graphics Statistical Programming Statistical Thinking Strings Tips and Techniques vectorization Video
I began 2015 by compiling a list of popular articles from my blog in 2014. Although this "People's Choice" list contains many interesting articles, some of my favorites did not make the list. Today I present the "Editor's Choice" list of articles that deserve a second look. I've highlighted one […]Post a Comment
My colleague Robert Allison has a knack for finding fascinating data. Last week he did it again by locating data about how blood types and Rh factors vary among countries. He produced a series of eight world maps, each showing the prevalence of a blood type (A+, A-, B+, B-, […]Post a Comment
One of my presentations at SAS Global Forum 2014 was about the new heat map functions in SAS/IML 13.1. Over the summer I created a short video of my presentation, which gives an overview of visualizing matrices with heat maps, and describes how to choose colors for heat maps: If […]Post a Comment
Have you ever looked as a statistical graph that uses bright garish colors and thought, "Why in the world did that guy choose those awful colors?" Don't be "that guy"! Your choice of colors for a graph can make a huge difference in how well your visualization is perceived by […]Post a Comment
In a previous article I introduced the HEATMAPCONT subroutine in SAS/IML 13.1, which makes it easy to visualize matrices by using heat maps with continuous color ramps. This article introduces a companion subroutine. The HEATMAPDISC subroutine, which also requires SAS/IML 13.1, is designed to visualize matrices that have a small […]Post a Comment
While at JSM 2014 in Boston, a statistician asked me whether it was possible to create a "customized bin plot" in SAS. When I asked for more information, she told me that she has a large data set. She wants to visualize the data, but a scatter plot is not […]Post a Comment
In a previous blog post I showed how to order a set of variables by a statistic. After reshaping data, you can create a graph that contains box plots for many variables. Ordering the variables by some statistic (mean, median, variance,...) helps to differentiate and distinguish the variables. You can […]Post a Comment
When I create a graph of data that contains a categorical variable, I rarely want to display the categories in alphabetical order. For example, the box plot to the left is a plot of 10 standardized variables where the variables are ordered by their median value. The ordering makes it […]Post a Comment
While I was working on my recent blog post about two-dimensional binning, a colleague asked whether I would be discussing "the new hexagonal binning method that was added to the SURVEYREG procedure in SAS/STAT 13.2." I was intrigued: I was not aware that hexagonal binning had been added to a […]Post a Comment
In a previous blog post, I showed how to use the graph template language (GTL) in SAS to create heat maps with a continuous color ramp. SAS/IML 13.1 includes the HEATMAPCONT subroutine, which makes it easy to create heat maps with continuous color ramps from SAS/IML matrices. Typical usage includes […]Post a Comment